Evidence map›Paper›PMID 36366153›Full record

ArticleSensors (Basel, Switzerland)2022

A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal.

Farah Masood, Milan Sharma, Davleen Mand, Shanker Nesathurai, Heather A Simmons, Kevin Brunner, Dane R Schalk, John B Sledge, Hussein A Abdullah

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. ShuffleLeNet architecture for spinal cord injury classification and level detection.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026
    Article
  3. Article
  4. Article
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Farah MasoodSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.ORCID 0000-0003-3955-8012
Milan SharmaSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Davleen MandSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Shanker NesathuraiThe Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.
Heather A SimmonsThe Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.ORCID 0000-0002-4862-7289
Kevin BrunnerThe Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.ORCID 0000-0003-2620-2666
Dane R SchalkThe Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, WI 53715, USA.
John B SledgeThe Lafayette Bone and Joint Clinic, Lafayette, LA 70508, USA.ORCID 0000-0002-7704-500X
Hussein A AbdullahSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.ORCID 0000-0002-1716-3186

Funding

WNPRC Supplemental Request for Nonhuman Primate Enclosures to Equip HIV/AIDS-Related Research FacilitiesP51OD011106 · OD · UNIVERSITY OF WISCONSIN-MADISON · PI Dorota A. Grejner-Brzezinska · 2012 to 2026
$150.7M
ZETA CHAIN OF T CELL RECEPTOR INTERACTS W/ NEF OF SIV &HIV2P51RR000168 · NCRR · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI ROWLETT, JAMES K · 1985 to 2011
$139.3M
NIH HHS 5P51RR000168NIH HHS P51 OD011106NIH HHS P51OD011106Research Facilities Improvement Program RR15459-01 and RR020141-01
6 · The paper itself

Abstract

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (

Indexed as

Deep LearningSpinal Cord InjuriesAnimalsElectromyographyMacaca fascicularisMachine LearningNeural Networks, Computerconvolutional neural networkdeep learningelectromyographyk-nearest neighborsmachine learningnon-human primatespinal cord injury

Identifiers

PMID36366153
PMCPMC9657335

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.